ABSTRACT
The field of computational intelligence has evolved as a sub-branch of the artificial intelligence domain, with the ultimate goal of developing machines that can think as humans. Specifically, the supreme achievement in this field would be to mimic or exceed human cognitive capabilities such as reasoning, understanding and even learning. Computational intelligence includes neural networks, global optimization algorithms (such as evolutionary algorithms), decision trees/forests, support vector machines, and many other techniques. These techniques have been successfully applied to a variety of applications, for the solution of real-world problems. Among them, financial forecasting is one of the fields, where computational intelligence has been used extensively. This chapter introduces the fundamental aspects of the key components of advanced computational intelligence techniques, emphasizing supervised learning as it forms the main category of computational intelligence paradigms dealing with financial engineering problems. It presents a comprehensive overview of various tools of computational intelligence, focusing on recent advances, open problems and future research directions.
